[AI]Why Microsoft is cutting roles despite strong earnings

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is cutting about 7,000 jobs, or 3% of its workforce.

The move isn’t about poor performance or falling revenue. It’s a clear shift in strategy—fewer layers, more engineers, and more investment in artificial intelligence.

The layoffs affect staff across divisions and global offices. But the bulk of those let go are in middle management and non-technical roles, a pattern showing up across tech. The message: reduce overhead, speed up product cycles, and make room for ******* AI spending.

The numbers behind the shift

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ended its latest quarter with $70.07 billion in revenue. That beat Wall Street estimates and shows strong business health, and the company plans to spend as much as $80 billion this fiscal year—mainly on data centres designed for training and running AI models.

That’s a big leap in infrastructure spending but it also explains why

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is trimming elsewhere.

AI models are compute-heavy and demand new types of hardware. Storage, cooling, and power need to scale: Building that capacity takes money, time, and fewer internal delays, and

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appears to be cutting anything that slows the push.

Management in the firing line

Most cuts hit middle managers and support staff. These are roles that help coordinate, review, and report—but don’t directly write code or design systems. While these positions have long helped large companies function, they’re now being seen as blockers to fast action.

Sources told

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that

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wants a higher ratio of technical staff to managers. This isn’t just about saving costs, it’s about reducing the number of people between engineers and final decisions.

Analyst Rishi Jaluria told the

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that tech giants like

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have “too many layers.” He said companies are trying to strip back bureaucracy as they chase AI leadership.

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has not publicly broken down which departments were most affected. But reports suggest LinkedIn, a

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subsidiary, saw job cuts as part of this broader shift.

Aligning with a broader industry trend

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isn’t the only company trimming management, as

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,

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, and Meta have all done similarly. They’re removing layers and pushing more decisions closer to those building the product.

For

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, the changes come after several earlier rounds of cuts. In early 2024, the company laid off around 2,000 workers in performance-based trims. This new wave is different as it targets structure, not staff output.

$80 billion on AI infrastructure

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’s investment plan puts AI at the centre of its growth. According to

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, the company wants to spend up to $80 billion in fiscal 2025, much of it going toward AI-enabled data centres.

These centres power large language models, natural language tools, and enterprise AI systems. Without them, even the best models won’t run at scale.

The company’s move shows how serious it is about owning the AI backbone. This is about more than software updates, it’s about physical hardware, cloud capacity, and tight control over how AI gets built and used.

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’s early partnership with OpenAI gave it a jumpstart, but

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, Meta,

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, and Apple are all making big AI moves.

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appears to be betting that first-mover advantage is only as strong as the infrastructure behind it.

Employee reactions reflect mixed sentiment

As with most layoffs, employee reactions vary. Some posts on social media reflect understanding, others voice concern about job security and team stability.

Several ex-employees described the mood as “tense but expected.” Many said they had been preparing for changes since

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’s 2024 performance cuts.

Some worry that too much focus on AI will weaken support roles, and others believe cutting managers will create confusion rather than clarity.

Still, public sentiment shows a growing acceptance that AI is changing what jobs look like—even at the biggest firms.

What this means for the industry

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’s restructuring sets a tone: Strong revenue no longer guarantees job security, and growth in AI now drives org charts, not the other way around.

Middle management is no longer safe, and non-technical roles must prove direct value to AI goals. Even product teams may face more pressure to automate or streamline. For employees, the message is clear. Learn how AI fits your job—or risk being cut from the plan.

For other tech firms,

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’s strategy may serve as a roadmap. Spending more on AI means spending less elsewhere. and many companies will likely follow that playbook to stay competitive.

Long-term questions remain

The short-term logic is clear.

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is cutting structure to fund AI growth. But over time, companies will need to balance innovation with internal support.

Removing middle managers may speed up some work, but it can also reduce mentorship, training, and context—things that help teams stay aligned.

AI may need more data and compute. But people still build the tools, ask the right questions, and set the goals. How companies treat those people now will shape how well they compete later.

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